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Thomas Weinberger

2 accepted papers

2025

Which Algorithms Have Tight Generalization Bounds?

NeurIPS 2025spotlight

We study which machine learning algorithms have tight generalization bounds with respect to a given collection of population distributions. Our results build on and extend the recent work of Gastpar et al. (2023). First, we present conditions that preclude the existence of tight generalization bound…

Cited by 0SourceScholar
2024

Fantastic Generalization Measures are Nowhere to be Found

ICLR 2024poster

We study the notion of a generalization bound being _uniformly tight_, meaning that the difference between the bound and the population loss is small for all learning algorithms and all population distributions. Numerous generalization bounds have been proposed in the literature as potential explana…

Cited by 12SourcePDFScholar